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XPostsClassificationModel

Text Classification
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roberta
Generated from Trainer
text-embeddings-inference
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  2. model.safetensors +1 -1
  3. runs/Nov11_17-52-29_1d799deba2c2/events.out.tfevents.1762883550.1d799deba2c2.4083.0 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: FacebookAI/roberta-large
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: XPostsClassificationModel
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # XPostsClassificationModel
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+
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+ This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5237
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+ - Accuracy: 0.9195
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 1.1653 | 1.0526 | 20 | 1.0058 | 0.4228 |
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+ | 0.6361 | 2.1053 | 40 | 0.5189 | 0.7383 |
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+ | 0.2347 | 3.1579 | 60 | 0.2813 | 0.8792 |
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+ | 0.2686 | 4.2105 | 80 | 0.2233 | 0.8993 |
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+ | 0.0763 | 5.2632 | 100 | 0.5500 | 0.8389 |
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+ | 0.0284 | 6.3158 | 120 | 0.6369 | 0.8389 |
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+ | 0.0084 | 7.3684 | 140 | 0.4523 | 0.8591 |
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+ | 0.0038 | 8.4211 | 160 | 0.8007 | 0.8456 |
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+ | 0.0289 | 9.4737 | 180 | 0.5008 | 0.9060 |
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+ | 0.0009 | 10.5263 | 200 | 0.7118 | 0.8792 |
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+ | 0.0068 | 11.5789 | 220 | 0.4647 | 0.9128 |
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+ | 0.0131 | 12.6316 | 240 | 0.3912 | 0.9060 |
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+ | 0.0007 | 13.6842 | 260 | 0.5074 | 0.9195 |
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+ | 0.0003 | 14.7368 | 280 | 0.6823 | 0.9060 |
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+ | 0.0007 | 15.7895 | 300 | 0.3905 | 0.9195 |
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+ | 0.0018 | 16.8421 | 320 | 0.4539 | 0.9195 |
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+ | 0.031 | 17.8947 | 340 | 0.7965 | 0.8993 |
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+ | 0.0336 | 18.9474 | 360 | 0.5107 | 0.8926 |
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+ | 0.0008 | 20.0 | 380 | 0.5105 | 0.8859 |
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+ | 0.0002 | 21.0526 | 400 | 0.4367 | 0.9060 |
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+ | 0.0002 | 22.1053 | 420 | 0.4576 | 0.9128 |
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+ | 0.0004 | 23.1579 | 440 | 0.4095 | 0.9195 |
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+ | 0.0003 | 24.2105 | 460 | 0.4776 | 0.9128 |
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+ | 0.0002 | 25.2632 | 480 | 0.4460 | 0.9128 |
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+ | 0.0001 | 26.3158 | 500 | 0.4092 | 0.9195 |
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+ | 0.0001 | 27.3684 | 520 | 0.5776 | 0.8859 |
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+ | 0.0053 | 28.4211 | 540 | 0.4901 | 0.9060 |
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+ | 0.0124 | 29.4737 | 560 | 0.5235 | 0.9128 |
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+ | 0.0003 | 30.5263 | 580 | 0.4890 | 0.9262 |
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+ | 0.0033 | 31.5789 | 600 | 0.4679 | 0.8993 |
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+ | 0.0001 | 32.6316 | 620 | 0.5067 | 0.9060 |
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+ | 0.0001 | 33.6842 | 640 | 0.5433 | 0.9128 |
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+ | 0.0001 | 34.7368 | 660 | 0.5524 | 0.9128 |
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+ | 0.0001 | 35.7895 | 680 | 0.5494 | 0.9128 |
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+ | 0.0001 | 36.8421 | 700 | 0.4944 | 0.9060 |
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+ | 0.0001 | 37.8947 | 720 | 0.4902 | 0.9060 |
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+ | 0.0001 | 38.9474 | 740 | 0.4910 | 0.9060 |
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+ | 0.0001 | 40.0 | 760 | 0.5675 | 0.9128 |
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+ | 0.0001 | 41.0526 | 780 | 0.6314 | 0.8926 |
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+ | 0.0001 | 42.1053 | 800 | 0.6384 | 0.8926 |
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+ | 0.0001 | 43.1579 | 820 | 0.6317 | 0.8926 |
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+ | 0.0001 | 44.2105 | 840 | 0.5489 | 0.9195 |
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+ | 0.0001 | 45.2632 | 860 | 0.5316 | 0.9195 |
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+ | 0.0001 | 46.3158 | 880 | 0.5325 | 0.9195 |
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+ | 0.0001 | 47.3684 | 900 | 0.5332 | 0.9195 |
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+ | 0.0001 | 48.4211 | 920 | 0.5244 | 0.9195 |
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+ | 0.0001 | 49.4737 | 940 | 0.5237 | 0.9195 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.1
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 4.4.1
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+ - Tokenizers 0.22.1
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